AIMC Topic: Fluorodeoxyglucose F18

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F-FDG PET/CT-Guided Real-Time Automated Robotic Arm-Assisted Needle Navigation for Percutaneous Biopsy of Hypermetabolic Bone Lesions: Diagnostic Performance and Clinical Impact.

AJR. American journal of roentgenology
OBJECTIVE: The purpose of this study is to establish the feasibility, safety, diagnostic performance, and clinical impact of real-time intraprocedural F-FDG PET/CT-guided automated robotic arm-assisted biopsy of hypermetabolic marrow or bone lesions.

Convolutional Neural Networks Promising in Lung Cancer T-Parameter Assessment on Baseline FDG-PET/CT.

Contrast media & molecular imaging
AIM: To develop an algorithm, based on convolutional neural network (CNN), for the classification of lung cancer lesions as T1-T2 or T3-T4 on staging fluorodeoxyglucose positron emission tomography (FDG-PET)/CT images.

Machine learning identified an Alzheimer's disease-related FDG-PET pattern which is also expressed in Lewy body dementia and Parkinson's disease dementia.

Scientific reports
Utilizing the publicly available neuroimaging database enabled by Alzheimer's disease Neuroimaging Initiative (ADNI; http://adni.loni.usc.edu/ ), we have compared the performance of automated classification algorithms that differentiate AD vs. normal...

Reproducible evaluation of classification methods in Alzheimer's disease: Framework and application to MRI and PET data.

NeuroImage
A large number of papers have introduced novel machine learning and feature extraction methods for automatic classification of Alzheimer's disease (AD). However, while the vast majority of these works use the public dataset ADNI for evaluation, they ...

Multilevel Feature Representation of FDG-PET Brain Images for Diagnosing Alzheimer's Disease.

IEEE journal of biomedical and health informatics
Using a single imaging modality to diagnose Alzheimer's disease (AD) or mild cognitive impairment (MCI) is a challenging task. FluoroDeoxyGlucose Positron Emission Tomography (FDG-PET) is an important and effective modality used for that purpose. In ...

Global temporal lobe asymmetry as a semi-quantitative imaging biomarker for temporal lobe epilepsy lateralization: A machine learning classification study.

Hellenic journal of nuclear medicine
OBJECTIVE: The purpose of this study was to evaluate the utility of global semi-quantitative analysis via fluorine-18-flurodeoxyglucose positron emission tomography (F-FDG PET) at lateralizing seizure foci and diagnosing patients with unilateral temp...

Multicenter validation of [F]-FDG PET and support-vector machine discriminant analysis in automatically classifying patients with amyotrophic lateral sclerosis versus controls.

Amyotrophic lateral sclerosis & frontotemporal degeneration
OBJECTIVE: F-Fluorodeoxyglucose (F-FDG) positron emission tomography (PET) single-center studies using support vector machine (SVM) approach to differentiate amyotrophic lateral sclerosis (ALS) from controls have shown high overall accuracy on an ind...

Multiscale deep neural network based analysis of FDG-PET images for the early diagnosis of Alzheimer's disease.

Medical image analysis
Alzheimer's disease (AD) is one of the most common neurodegenerative diseases with a commonly seen prodromal mild cognitive impairment (MCI) phase where memory loss is the main complaint progressively worsening with behavior issues and poor self-care...